The conventional approach to power distribution grid voltage control is based on techniques developed about 70 years ago, one goal of which is to control demand (either raising or lowering demand). In recent years, highly complex and expensive systems have been required to implement improved effective voltage control and conservation voltage reduction (CVR) based demand reduction, one example of which is power distribution grid voltage control. Typically, utilities operate in a narrow band of 116-124 volts, even though level ‘A’ service allows for a range of 114-126 volts. The difficulty in adhering to a tight regulation band arises from normal fluctuations in incoming line voltage at the substation, as well as load changes along the feeder. These changes cause the line voltage to vary, with utilities required to maintain voltage for consumers within specified bounds.
A primary purpose of voltage control is maintaining acceptable voltage levels, e.g., per the American National Standards Institute (ANSI) standards or similar standard setting organizations, at the service entrance of customers served by a feeder under all possible operating conditions. Electric utilities traditionally maintain distribution system voltage within the acceptable range using transformers with moveable taps that permit voltage adjustments under load. Other methods include de-energized tap changers (DETC) where the transformers are de-energized for changing the tap setting and then re-energized once the tap is changed. When utilizing the DETC method, the tap remains fixed once changed and the voltage is not actively regulated. Voltage regulators located in substations and on the lines, as well as substation transformers are commonly used for voltage control purposes. These transformers, sometimes referred to as Load Tap Changers (LTCs), and are equipped with a voltage-regulating controller that determines whether to raise or lower the transformer tap settings or leave the tap setting unchanged based on “local” voltage and load measurements.
With electric grid modernization strategies gaining importance and momentum as utilities push ahead to upgrade their aging infrastructure, Volt Var Control (VVC) has become an important tool to regulate voltage. However, current VVC tools can't deliver the needed performance benefits due to extreme voltage volatility at the edge of the grid, the inability of existing tools to see these conditions and characterize these voltage conditions accurately across the feeder. In the recent times, the cost of PV installation has dramatically reduced, which has consequently led to an increase in distributed photovoltaic voltage (PV) on electric distribution network. The increase in introduction of solar power can be attributed to an increase in the number of solar power utilities being formed to facilitate broad deployment of distributed energy technologies such as rooftop solar PV systems. For example, policies in some countries provide subsidies and incentivize the installation of residential and commercial solar PV systems through two mechanisms namely, feed-in tariffs (FIT) and net energy metering (NEM). The increased penetration of distributed PV systems may exacerbate these issues because the voltage fluctuations introduced by PV may consume the ANSI band and leave little room for VVC. FIG. 16 depicts an example of voltage volatility measured at a distribution grid edge over a number of days. Specifically, in the example in FIG. 16, volatility as high as 17% was measured.
VVC has been achieved using centralized optimization engines that control volts and VARs on the power grid using primary side assets. This is realized by changing the tap settings of LTCs and LVRs to achieve voltage control or by switching ON/OFF capacitor banks to achieve VAR control. The aim of these optimization engines is to ensure that voltages at the customer meters are maintained within a specified band e.g. ANSI C84.1 specifies 114V to 126V as the ANSI-A band.
Many of these existing primary assets are designed to handle grid voltage fluctuations at a rather slow rate (e.g., 30 sec to 15 minutes). Further, they are designed to switch or operate no more than a few times (e.g., 5-10 times a day) to ensure a long life. However, with more distributed PV on the electric grid causing high levels of variability, these primary assets may need to operate much more than designed. This overuse may effectively reduce the life expectancy of the primary assets.
One example solution used to manage some of this voltage volatility employs PV inverters that have the capability of regulating reactive power (leading and lagging) in addition to supplying real power generated from PV panels. A volt-VAR droop curve, similar to the curve illustrated in FIG. 17, may be used by control logic to control the reactive power output from the smart inverters to maintain voltages within the specified limits. Theoretically this curve ensures that the right control actions are taken to maintain local voltage within the specified limits. However, as illustrated in FIG. 17, the curve spans a wide range around the normal voltage (e.g., +/−3% to 5% in many cases). Thus, most of the specified band is consumed for achieving the volt-VAR control objective. Also, introducing large numbers of inverters on the grid may increase instability and operational problems related to unexpected interaction between inverters (e.g., infighting).